Methods for objective characterization, recognition and classification of cells by computer analysis of their digitized images will be extended to the next higher level to the classification of entire cytodiagnostic samples. Sample profiles characterizing the cellular composition, state, degree of atypia, and developmental trends of cell samples taken from patients with various clinical cytologic conditions will be analyzed. The potential for the detection of prognostic clues will be explored. A base line study for a taxonomy of preneoplastic cytologic conditions will be made. Classification rules for sample profiles from patients with conditions of cellular atypia will be developed. Work on the further development of the recognition of individual cells by the TICAS method will be continued. Recursive feature extraction methods, and new cell image representation by feature matrices with probabilistically defined elements will be implemented. The present proposal is a renewal application of the existing grant R01-CA-13271-08.